Demo Data from VLDB 2026 / reviewers in the wild / expert
Daniel Cameron
dblp:52/4459
· DBLP profile ↗
3ranked-venue papers
3as first author
2since 2021 · last 2022
0000-0002-0951-7116ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 2 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics
genomic variant analysis |
0.6 | 1 | 2022 | StructuralVariantAnnotation: a R/Bioconductor foundation for a caller-agnostic structural variant software ecosystem · Bioinform. 2022 |
Bioinformatics and computational biology › sequence analysis › sequence variation analysis
structural variant annotation |
0.6 | 1 | 2022 | StructuralVariantAnnotation: a R/Bioconductor foundation for a caller-agnostic structural variant software ecosystem · Bioinform. 2022 |
Bioinformatics and computational biology
cancer genomics |
0.5 | 1 | 2021 | VIRUSBreakend: Viral Integration Recognition Using Single Breakends · Bioinform. 2021 |
Bioinformatics and computational biology › genomics › viral genomics
viral integration detection |
0.5 | 1 | 2021 | VIRUSBreakend: Viral Integration Recognition Using Single Breakends · Bioinform. 2021 |
Bioinformatics and computational biology › comparative genomics
genome rearrangement |
0.2 | 1 | 2022 | StructuralVariantAnnotation: a R/Bioconductor foundation for a caller-agnostic structural variant software ecosystem · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
r · 0.6bioconductor · 0.6variant calling · 0.5de novo assembly · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | StructuralVariantAnnotation: a R/Bioconductor foundation for a caller-agnostic structural variant software ecosystemabstractSUMMARY: StructuralVariantAnnotation is an R/Bioconductor package that provides a framework for decoupling downstream analysis of structural variant breakpoints from upstream variant calling methods. It standardizes the representational format from BEDPE, or any of the three different notations supported by VCF into a breakpoint GRanges data structure suitable for use by the wider Bioconductor ecosystem. It handles both transitive breakpoints and duplication/insertion notational differences of identical variants-both common scenarios when comparing short/long read-based call sets that confound downstream analysis. StructuralVariantAnnotation provides the caller-agnostic foundation needed for a R/Bioconductor ecosystem of structural variant annotation, classification and interpretation tools able to handle both simple and complex genomic rearrangements. AVAILABILITY AND IMPLEMENTATION: StructuralVariantAnnotation is implemented in R and available for download as the Bioconductor StructuralVariantAnnotation package. Details can be found at https://www.bioconductor.org/packages/release/bioc/html/StructuralVariantAnnotation.html. It has been released under a GPL license. Daniel Cameron, Ruining Dong, Anthony T. Papenfuss |
Bioinform. | 1 |
| 2021 | VIRUSBreakend: Viral Integration Recognition Using Single BreakendsabstractMOTIVATION: Integration of viruses into infected host cell DNA can cause DNA damage and disrupt genes. Recent cost reductions and growth of whole genome sequencing has produced a wealth of data in which viral presence and integration detection is possible. While key research and clinically relevant insights can be uncovered, existing software has not achieved widespread adoption, limited in part due to high computational costs, the inability to detect a wide range of viruses, as well as precision and sensitivity. RESULTS: Here, we describe VIRUSBreakend, a high-speed tool that identifies viral DNA presence and genomic integration. It utilizes single breakends, breakpoints in which only one side can be unambiguously placed, in a novel virus-centric variant calling and assembly approach to identify viral integrations with high sensitivity and a near-zero false discovery rate. VIRUSBreakend detects viral integrations anywhere in the host genome including regions such as centromeres and telomeres unable to be called by existing tools. Applying VIRUSBreakend to a large metastatic cancer cohort, we demonstrate that it can reliably detect clinically relevant viral presence and integration including HPV, HBV, MCPyV, EBV and HHV-8. AVAILABILITY AND IMPLEMENTATION: VIRUSBreakend is part of the Genomic Rearrangement IDentification Software Suite (GRIDSS). It is available under a GPLv3 license from https://github.com/PapenfussLab/VIRUSBreakend. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Daniel Cameron, Nina Jacobs, Paul Roepman, Peter Priestley, Edwin Cuppen, Anthony T. Papenfuss |
Bioinform. | 1 |
| 2003 | Knowledge-Based Autonomous Dynamic Colour Calibration
Daniel Cameron, Nick Barnes |
RoboCup | 1 |